mindspore.ops.renorm
- mindspore.ops.renorm(input, p, axis, maxnorm)[source]
Renormalizes the sub-tensors along dimension axis, and each sub-tensor's p-norm should not exceed the maxnorm. The values of current sub-tensor don't need change if the p-norm of the sub-tensor is less than maxnorm. Otherwise the sub-tensor needs to be modified to the original value of the corresponding position divided by the p-norm of the substensor and then multiplied by maxnorm.
- Parameters
- Returns
Tensor, has the same dtype and shape as input.
- Raises
TypeError – If dtype of p is not int.
TypeError – If dtype of axis is not int.
TypeError – If dtype of maxnorm is not float32.
ValueError – If the value of p less than 1.
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> import mindspore >>> import numpy as np >>> from mindspore import Tensor, ops >>> x = Tensor(np.array([[1, 1, 1], [2, 2, 2], [3, 3, 3]]), mindspore.float32) >>> y = ops.renorm(x, p=1, axis=0, maxnorm=5.) >>> print(y) [[1. 1. 1. ] [1.6666666 1.6666666 1.6666666 ] [1.6666667 1.6666667 1.6666667 ]]